The cross-entropy method in multi-objective optimisation: An assessment
Solving multi-objective problems requires the evaluation of two or more conflicting objective functions, which often demands a high amount of computational power. This demand increases rapidly when estimating values for objective functions of dynamic, stochastic problems, since a number of observati...
| Main Authors: | , |
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| Format: | Journal Article |
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Elsevier BV * North-Holland
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/18384 |
| _version_ | 1848749729749401600 |
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| author | Bekker, J. Aldrich, Chris |
| author_facet | Bekker, J. Aldrich, Chris |
| author_sort | Bekker, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Solving multi-objective problems requires the evaluation of two or more conflicting objective functions, which often demands a high amount of computational power. This demand increases rapidly when estimating values for objective functions of dynamic, stochastic problems, since a number of observations are needed for each evaluation set, of which there could be many. Computer simulation applications of real-world optimisations often suffer due to this phenomenon. Evolutionary algorithms are often applied to multi-objective problems. In this article, the cross-entropy method is proposed as an alternative, since it has been proven to converge quickly in the case of single-objective optimisation problems. We adapted the basic cross-entropy method for multi-objective optimisation and applied the proposed algorithm to known test problems. This was followed by an application to a dynamic, stochastic problem where a computer simulation model provides the objective function set. The results show that acceptable results can be obtained while doing relatively few evaluations. |
| first_indexed | 2025-11-14T07:25:34Z |
| format | Journal Article |
| id | curtin-20.500.11937-18384 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:25:34Z |
| publishDate | 2011 |
| publisher | Elsevier BV * North-Holland |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-183842017-09-13T16:07:34Z The cross-entropy method in multi-objective optimisation: An assessment Bekker, J. Aldrich, Chris Simulation - Cross-entropy - Stochastic processes - Multi-objective optimisation - Pareto-optimal Solving multi-objective problems requires the evaluation of two or more conflicting objective functions, which often demands a high amount of computational power. This demand increases rapidly when estimating values for objective functions of dynamic, stochastic problems, since a number of observations are needed for each evaluation set, of which there could be many. Computer simulation applications of real-world optimisations often suffer due to this phenomenon. Evolutionary algorithms are often applied to multi-objective problems. In this article, the cross-entropy method is proposed as an alternative, since it has been proven to converge quickly in the case of single-objective optimisation problems. We adapted the basic cross-entropy method for multi-objective optimisation and applied the proposed algorithm to known test problems. This was followed by an application to a dynamic, stochastic problem where a computer simulation model provides the objective function set. The results show that acceptable results can be obtained while doing relatively few evaluations. 2011 Journal Article http://hdl.handle.net/20.500.11937/18384 10.1016/j.ejor.2010.10.028 Elsevier BV * North-Holland restricted |
| spellingShingle | Simulation - Cross-entropy - Stochastic processes - Multi-objective optimisation - Pareto-optimal Bekker, J. Aldrich, Chris The cross-entropy method in multi-objective optimisation: An assessment |
| title | The cross-entropy method in multi-objective optimisation: An assessment |
| title_full | The cross-entropy method in multi-objective optimisation: An assessment |
| title_fullStr | The cross-entropy method in multi-objective optimisation: An assessment |
| title_full_unstemmed | The cross-entropy method in multi-objective optimisation: An assessment |
| title_short | The cross-entropy method in multi-objective optimisation: An assessment |
| title_sort | cross-entropy method in multi-objective optimisation: an assessment |
| topic | Simulation - Cross-entropy - Stochastic processes - Multi-objective optimisation - Pareto-optimal |
| url | http://hdl.handle.net/20.500.11937/18384 |